Solving the Problem of Large-Scale Optimal Scheduling of Distributed Energy Resources in Smart Grids Using an Improved Variable Neighborhood Search

Ramli, Makbul A.M.; Bouchekara, Houssem R. E. H.

doi:10.1109/access.2020.2986895

Cited by 8 publications

(4 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The VNS algorithm is a metaheuristic that combines search strategies with systematic neighborhood changes to explore the search space of a problem efficiently, which has been used in specialized literature with the Fibonacci search method (FSM) to solve large-scale issues efficiently [34]. VNS is based on the principle that a local optimum within a given neighborhood is not necessarily one within another.…”

Section: B Variable Neighborhood Searchmentioning

confidence: 99%

A Novel Methodology for Reducing Excessive Reactive Power Consumption Penalties for Photovoltaic Prosumers

Vargas,

Gabriel Borges,

Vicentini

et al. 2024

IEEE Access

View full text Add to dashboard Cite

The present paper proposes a new methodology to solve a problem in the literature in which a consumer becomes eligible for reactive power excess charging (RPEC) after installing a photovoltaic (PV) system, even if its reactive demand has not changed. This problem mainly affects this kind of consumer, which is known as PV prosumers, in countries where the power factor at the point of common coupling (PCC) is used as the main parameter in calculating reactive power excess charges instead of directly pricing the surplus reactive energy delivered from the distribution network. The classical approaches to reducing or eliminating RPEC are based on providing reactive power within the consumer's installations from their PV inverters and their capacitor banks. However, the solutions presented require optimization studies since the costs of producing reactive energy can be even higher than the penalties involved. In this context, we developed a new hourly-based optimization model for the RPEC problem based on the variable neighborhood search meta-heuristic and the Fibonacci search method. In addition, we apply the proposed methodology to two medium voltage prosumers in Santo André, Brazil. The results showed the proposal's effectiveness, mitigating RPEC and minimizing the prosumers' electricity bills without installing new equipment to supply their reactive demand. The best results were found when reactive power was delivered by the capacitor bank and PV inverters simultaneously rather than applying these solutions separately. The proposed hourly-based correction method can help in day-ahead energy management, avoiding premature wear from switching the consumer's reactive power compensation equipment switches. Also, the methodology proposal improved the power factor at the utility substation, which benefits the power distribution systems.

show abstract

Section: B Variable Neighborhood Searchmentioning

confidence: 99%

A Novel Methodology for Reducing Excessive Reactive Power Consumption Penalties for Photovoltaic Prosumers

Vargas,

Gabriel Borges,

Vicentini

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Management of excess power generation to ensure supply of demand and security of power supply [95] Daily market -Adjusting the price of energy trading in the future market-reducing the cost of supply and demand imbalance [96] Real-time market -Management of power fluctuations between supply and demand and network security…”

Section: Referencementioning

confidence: 99%

“…In addition, it provides a smart web page and mobile app for VPP users. A new concept of IoT in the VPP is presented in [96]. The main goal of providing the IoT in VPP is the intelligent control of power transmission in high voltage lines at a low cost.…”

Section: Communication and Information Challenges Of Vppsmentioning

confidence: 99%

Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities

et al. 2022

View full text Add to dashboard Cite

High penetration of distributed generation and renewable energy sources in power systems has created control challenges in the network, which requires the coordinated management of these resources. Using virtual power plants (VPPs) on a large scale has solved these challenges to a significant extent. VPPs can be considered systems consisting of distributed generations, energy storage, controllable loads, electric vehicles (EVs), and other types of resources to provide energy and ancillary services. VPPs face various challenges such as energy management, operation, resource uncertainty, participation in electricity markets, etc. This paper discusses an overview of the basic challenges of VPPs, including control and communication issues, electricity markets, its different models, and energy management issues. The main purpose is to investigate the performance of VPP in different markets, energy management of VPP in different operating conditions and strategies, and compare different planning methods for VPP. Note that the application of blockchain to control and improve VPP performance has been investigated, taking into account the different layers of this technology.

show abstract

“…The VNS algorithm has been shown to perform well in various problems. Its applications include the max-cut combinatorial problem [17,18], the scheduling problem [19,20], the layouting problem [21], the vehicle routing problem [22], and the multiprocessor scheduling problem with communication delays [23]. It has, also, been used to tune proportional-integral-derivative controllers in cyber-physical systems [24].…”

Section: Introductionmentioning

confidence: 99%

Constructing the Neighborhood Structure of VNS Based on Binomial Distribution for Solving QUBO Problems

Pambudi

Kawamura

2022

Algorithms

View full text Add to dashboard Cite

The quadratic unconstrained binary optimization (QUBO) problem is categorized as an NP-hard combinatorial optimization problem. The variable neighborhood search (VNS) algorithm is one of the leading algorithms used to solve QUBO problems. As neighborhood structure change is the central concept in the VNS algorithm, the design of the neighborhood structure is crucial. This paper presents a modified VNS algorithm called “B-VNS”, which can be used to solve QUBO problems. A binomial trial was used to construct the neighborhood structure, and this was used with the aim of reducing computation time. The B-VNS and VNS algorithms were tested on standard QUBO problems from Glover and Beasley, on standard max-cut problems from Helmberg–Rendl, and on those proposed by Burer, Monteiro, and Zhang. Finally, Mann–Whitney tests were conducted using α=0.05, to statistically compare the performance of the two algorithms. It was shown that the B-VNS and VNS algorithms are able to provide good solutions, but the B-VNS algorithm runs substantially faster. Furthermore, the B-VNS algorithm performed the best in all of the max-cut problems, regardless of problem size, and it performed the best in QUBO problems, with sizes less than 500. The results suggest that the use of binomial distribution, to construct the neighborhood structure, has the potential for further development.

show abstract

Solving the Problem of Large-Scale Optimal Scheduling of Distributed Energy Resources in Smart Grids Using an Improved Variable Neighborhood Search

Cited by 8 publications

References 51 publications

A Novel Methodology for Reducing Excessive Reactive Power Consumption Penalties for Photovoltaic Prosumers

A Novel Methodology for Reducing Excessive Reactive Power Consumption Penalties for Photovoltaic Prosumers

Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities

Constructing the Neighborhood Structure of VNS Based on Binomial Distribution for Solving QUBO Problems

Contact Info

Product

Resources

About